96 PICTURE location – Using home location data from the electronic health record for research and improved clinical care
IntroductionHome location data analyses can support research and help improve patient experience. The home location of Great Ormond Street Hospital (GOSH) patients, stored in the Electronic Health Record (EHR), can be used to generate the geographical distribution of disease and symptoms, and explor...
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Veröffentlicht in: | BMJ paediatrics open 2023-12, Vol.7 (Suppl 2), p.A15-A15 |
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Zusammenfassung: | IntroductionHome location data analyses can support research and help improve patient experience. The home location of Great Ormond Street Hospital (GOSH) patients, stored in the Electronic Health Record (EHR), can be used to generate the geographical distribution of disease and symptoms, and explore associations between cohorts and external data such as the Index of Multiple Deprivation (IMD).MethodsWe have made home location data available to PICTURE, the GOSH DRIVE clinical informatics platform, and have linked it to IMD data. We used the cohort builder and analytics capabilities of PICTURE to generate location maps and summarise and visualise the IMD distribution and the time and distance between the patients’ home and GOSH.The standard EHR data extraction processes developed by the GOSH Digital Research Environment (DRE) and used by PICTURE as well as PICTURE’s generalisable components allowed us to generate location-based analyses for a wide range of cohorts.We present a proof-of-concept (POC) application using a cohort of patients seen at the Nephrology specialty. The POC version was developed in R and Shiny using Leaflet and the OpenStreetMap-Based Routing Service OSRM.ResultsIn the GOSH nephrology cohort, the median (Q1-Q3) travel distance and travel time between patients’ home district and GOSH was 64km (23-125) and 60 minutes (31-99), respectively. Out of 779 patients with home location data that could be mapped to the IMD data, 138 (17.7%) lived in regions that fall within the 3rd IMD decile (1st being the most deprived), the most common decile in this cohort.ConclusionThis POC application of the PICTURE Location component demonstrates that we can use PICTURE to generate reproducible location-based analyses and potentially insightful outputs. Further work will focus on a wider range of applications and on linking the home location to more external data sources including air quality data.Acknowledgements for funding or supportThis work is supported by the NIHR GOSH BRC. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. This work is supported by the Great Ormond Street Hospital Children’s Charity. |
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ISSN: | 2399-9772 |
DOI: | 10.1136/bmjpo-2023-GOSH.33 |